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HOG를 이용한 손 형태 영상 인식
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 신현철 | - |
| dc.date.accessioned | 2021-06-23T10:41:26Z | - |
| dc.date.available | 2021-06-23T10:41:26Z | - |
| dc.date.created | 2021-02-18 | - |
| dc.date.issued | 2011-06 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/37375 | - |
| dc.description.abstract | Histograms of Oriented Gradients (HOG) were successfully used for the detection of human beings. In this paper, we adopted the HOG to recognize hand gestures. First, we find the gradient vectors from input images and make a histogram for each cell. Then support vector machine is used to recognize hand gestures. Currently, a single hand gesture or two hand gestures in an image can be recognized. The hand gestures can be used to give commands to computes or other equipments. Experimental results show 98 ~ 99% recognition rate for normalized images and 94 ~ 98% recognition rate for non-normalized images, for three hand gestures. When two hand gestures are shown in an image 90% recognition rate is achieved. | - |
| dc.publisher | 대한전자공학회 | - |
| dc.title | HOG를 이용한 손 형태 영상 인식 | - |
| dc.title.alternative | Hand Gesture Recognition by Using Histograms of Oriented Gradients | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | 신현철 | - |
| dc.identifier.bibliographicCitation | 대한전자공학회 하계학술대회, v.34권, no.1호, pp.761 - 764 | - |
| dc.relation.isPartOf | 대한전자공학회 하계학술대회 | - |
| dc.citation.title | 대한전자공학회 하계학술대회 | - |
| dc.citation.volume | 34권 | - |
| dc.citation.number | 1호 | - |
| dc.citation.startPage | 761 | - |
| dc.citation.endPage | 764 | - |
| dc.type.rims | ART | - |
| dc.description.journalClass | 3 | - |
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